Extracellular RNA Expression Biomarkers in Osteoarthritis Disease and Progression

骨关节炎疾病和进展中的细胞外 RNA 表达生物标志物

基本信息

批准号：
10593308
负责人：
Thomas Michael Best
金额：
$ 20.05万
依托单位：
UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-02-22 至 2025-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10593308
关键词：
Address Affect Age American Architecture Biochemical Bioinformatics Biological Biological Assay Biological Markers Biological Specimen Banks Body mass index Categories Chronic Disease Classification Clinical Clinical Data Cohort Studies Complex Data Degenerative polyarthritis Development Diagnosis Diagnostic Disease Disease Progression Failure Gene Expression Profile Genes Genetic Genetic Markers Genetic Techniques Genetic Transcription Genomics Heart Diseases Heterogeneity High-Throughput RNA Sequencing Image Incidence Individual Knee Osteoarthritis Magnetic Resonance Imaging Malignant Neoplasms Measures Methodology Methods MicroRNAs Molecular Molecular Genetics Molecular Profiling Multiple Sclerosis Pain Pathway interactions Patients Pattern Phenotype Physiological Processes Plasma Population Prevalence Public Health Questionnaires RNA Resources Risk Factors Roentgen Rays Role Sampling Signaling Molecule Statistical Data Interpretation Stress Symptoms Therapeutic Therapeutic Intervention Time Tissues aging population arthropathies biomarker identification clinical data repository clinical phenotype clinical subtypes cohort disease heterogeneity disorder risk disorder subtype effusion experimental study extracellular functional genomics genomic signature insight joint destruction molecular marker muscle strength novel pain symptom precision medicine prevent prognostic progression marker prospective radiological imaging risk stratification sex specific biomarkers targeted treatment treatment strategy

项目摘要

PROJECT SUMMARY Osteoarthritis (OA) is a progressive and degenerative joint disease with an increasing prevalence in the aging population for which existing treatments targeting the primary symptom of pain are only minimally successful. The manifestation of OA is heterogeneous with symptomology differing across individuals. This disease heterogeneity has made identification of reliable and consistent molecular biomarkers elusive. This has in part hindered the progress toward development of specific therapeutic treatments. Therefore, the identification of specific biomarkers of OA clinical phenotypes and longitudinal changes over disease progression is required. To begin addressing this issue, here we propose an initiative for the discovery of plasma extracellular RNA (exRNA) expression signatures genomic signatures of OA among diverse clinical and progressive phenotypes. exRNA has been demonstrated in a variety of complex diseases to have prognostic and biological value. The experiments will utilize the Osteoarthritis Initiative (OAI) which is a prospective, longitudinal multicenter cohort study of nearly 5000 subjects diagnosed with radiographic knee OA or at risk for the disease. We will first cluster the entire OAI cohort into distinct clinical phenotypes based on biochemical assays, imaging data, and clinical symptom questionnaires and identify exRNA signatures associated with those phenotypes using high throughput RNA sequencing (SA1). Furthermore, we will identify individuals with progressive OA defined as progression by radiograph changes over time as well as increasing pain over time. We will then generate longitudinal time- course profiles of exRNA expression to deduce biological mechanisms of that progression (SA2). By generating specific phenotype definitions, this study has increased power to identify molecular signatures of these OA groups. This will be an important step toward harnessing the value of functional genomics as a biomarker in the precision medicine of OA.

项目摘要骨关节炎（OA）是一种进行性和退化性关节疾病，衰老的患病率越来越高针对疼痛主要症状的现有治疗方法的种群仅在最低限度上成功。 OA的表现是异质的，症状学不同。这种疾病异质性已确定难以捉摸的可靠且一致的分子生物标志物。这部分有阻碍了开发特定治疗治疗的进展。因此，识别 OA临床表型的特定生物标志物和对疾病进展的纵向变化。为了开始解决这个问题，我们在这里提出了一项针对血浆细胞外RNA的计划（EXRNA）表达在不同的临床和进行性表型中OA的基因组特征。在各种复杂疾病中已证明EXRNA具有预后和生物学价值。这实验将利用骨关节炎倡议（OAI），这是一个前瞻性的，纵向的多中心队列研究近5000名诊断患有射线照相术或有疾病风险的受试者。我们将首先集群基于生化测定，成像数据和临床的整个OAI队列分为不同的临床表型症状问卷调查并识别使用高吞吐量与这些表型相关的EXRNA特征 RNA测序（SA1）。此外，我们将确定具有渐进式OA的个体被定义为通过 X光片随时间变化，并且随着时间的推移增加疼痛。然后，我们将产生纵向时间 - EXRNA表达的课程谱，以推断该进展的生物学机制（SA2）。通过产生特定的表型定义，这项研究具有增加识别分子特征的功率这些OA组。这将是利用功能基因组学价值作为一个的重要一步 OA精确医学中的生物标志物。